QUIZ TABLEAU - TCC-C01 UPDATED EXAM DUMPS ZIP

Quiz Tableau - TCC-C01 Updated Exam Dumps Zip

Quiz Tableau - TCC-C01 Updated Exam Dumps Zip

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Don't underestimate the difficulty level of the Tableau TCC-C01 certification exam because it is not easy to clear. You need to prepare real TCC-C01 exam questions to get success. If you do not prepare with actual TCC-C01 Questions, there are chances that you may fail the final and not get the TCC-C01 certification.

Tableau TCC-C01 Exam Syllabus Topics:

TopicDetails
Topic 1
  • Design and Troubleshoot Calculations and Workbooks: This domain evaluates the ability to design advanced analytics and troubleshoot workbooks. Candidates will implement calculations, optimize performance, and plan interactivity for dashboards while resolving performance issues.
Topic 2
  • Plan and Prepare Data Connections: This section focuses on planning data transformation and preparing connections, targeting Tableau-certified consultants. Candidates will recommend data storage methods, design row-level security structures, and troubleshoot complex data connection issues.
Topic 3
  • Establish Governance and Support Published Content: This section measures the skills of Tableau-certified consultants related to governance strategies within Tableau environments. Candidates will map governance requirements, recommend content access strategies, design administrative views, and identify external errors affecting performance.
Topic 4
  • Evaluate Current State: This domain measures the skills of Tableau-certified consultants in assessing the current analytics landscape. Candidates will evaluate existing reports and data structures to ensure alignment with business needs and recommend appropriate Tableau deployment options.

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Tableau Certified Consultant Sample Questions (Q21-Q26):

NEW QUESTION # 21
A client currently has a workbook with the table shown below.

Which method will produce the output for the Total Sales Value field for all the categories shown in the table?

  • A. Level of Detail (LOD) Calculation
  • B. A Window Function
  • C. MAX() Function
  • D. Quick Table Calculation

Answer: A

Explanation:
To calculate the Total Sales Value for all categories as displayed in the table, an LOD expression is ideal. An LOD calculation in Tableau allows you to compute values at the data level that is different from the view level. In this case, since the Total Sales Value appears consistent across different sub-categories within each category, an LOD expression can be used to fix the Total Sales Value irrespective of the sub-category detail.
Here's how to set it up:
* Go to the Calculations area by right-clicking in the data pane and selecting "Create Calculated Field".
* Enter a name for the calculation, such as "Total Sales Value".
* Enter the LOD expression:{ FIXED [Category] : SUM([Sales]) }. This calculation fixes the total sales to the category level, effectively summing sales for all sub-categories within each category, irrespective of how the data is broken down in the view.
* Drag this new calculated field into your visualization alongside the existing measures.
This method ensures that the Total Sales Value reflects the total for each category across all its sub-categories, matching the uniform values shown across different rows for each category in your table.
ReferencesThe explanation utilizes the concept of Level of Detail calculations in Tableau, which allows for advanced aggregations independent of the view level details. This concept is covered extensively in Tableau's official documentation and relevant training materials such as Tableau's online help resources.


NEW QUESTION # 22
A client wants to see the average number of orders per customer per month, broken down by region. The client has created the following calculated field:
Orders per Customer: {FIXED [Customer ID]: COUNTD([Order ID])}
The client then creates a line chart that plots AVG(Orders per Customer) over MONTH(Order Date) by Region. The numbers shown by this chart are far higher than the customer expects.
The client asks a consultant to rewrite the calculation so the result meets their expectation.
Which calculation should the consultant use?

  • A. {EXCLUDE [Customer ID]: COUNTD([Order ID])}
  • B. {FIXED [Customer ID], [Region], [Order Date]: COUNTD([Order ID])}
  • C. {FIXED [Customer ID], [Region]: COUNTD([Order ID])}
  • D. {INCLUDE [Customer ID]: COUNTD([Order ID])}

Answer: C

Explanation:
The calculation{FIXED [Customer ID], [Region]: COUNTD([Order ID])}is the correct one to use for this scenario. This Level of Detail (LOD) expression will calculate the distinct count of orders for each customer within each region, which is then averaged per month. This approach ensures that the average number of orders per customer is accurately calculated for each region and then broken down by month, aligning with the client's expectations.
References:The LOD expressions in Tableau allow for precise control over the level of detail at which calculations are performed, which is essential for accurate data analysis.The use of{FIXED}expressions to specify the granularity of the calculation is a common practice and is well-documented in Tableau's official resources12.
The initial calculation provided by the client likely overestimates the average number of orders per customer per month by region due to improper granularity control. The revised calculation must take into account both the customer and the region to correctly aggregate the data:
* FIXED Level of Detail Expression: This calculation uses a FIXED expression to count distinct order IDs for each customer within each region. This ensures that the count of orders is correctly grouped by both customer ID and region, addressing potential duplication or misaggregation issues.
* Accurate Aggregation: By specifying both [Customer ID] and [Region] in the FIXED expression, the calculation prevents the overcounting of orders that may appear if only customer ID was considered, especially when a customer could be ordering from multiple regions.
References:
* Level of Detail Expressions in Tableau: These expressions allow you to specify the level of granularity you need for your calculations, independent of the visualization's level of detail, thus offering precise control over data aggregation.


NEW QUESTION # 23
A client wants to flag orders that have sales higher than the regional average.
Which calculated field will produce the required result?

  • A. [Sales]
    >
    { FIXED [Order ID] : SUM([Sales]) }
  • B. { FIXED [Order ID] : SUM([Sales]) }
    >
    { FIXED [Region] : SUM([Sales]) }
  • C. { FIXED [Order ID] : SUM([Sales]) }
    >
    { FIXED [Region] : AVG({ FIXED [Order ID] : SUM([Sales]) }) }
  • D. { FIXED [Order ID] : SUM([Sales]) }
    >
    { INCLUDE [Region] : AVG({ FIXED [Order ID] : SUM([Sales]) }) }

Answer: C

Explanation:
To flag orders with sales higher than the regional average, the correct calculated field would compare the sum of sales for each order against the average sales of all orders within the same region:
* Correct Formula:{ FIXED [Order ID] : SUM([Sales]) } > { FIXED [Region] : AVG({ FIXED
[Order ID] : SUM([Sales]) }) }
* This calculation uses a Level of Detail (LOD) expression:
* The left part of the formula{ FIXED [Order ID] : SUM([Sales]) }calculates the total sales for each individual order.
* The right part{ FIXED [Region] : AVG({ FIXED [Order ID] : SUM([Sales]) }) }calculates the average sales per order within each region.
* The>operator is used to compare these two values to determine if the sales for each order exceed the regional average.
ReferencesThis formula utilizes Tableau's LOD expressions to perform complex comparisons across different dimensions of the data, as explained in Tableau's official training materials on LOD calculations.


NEW QUESTION # 24
A client is searching for ways to curate and document data in order to obtain data lineage. The client has a data source connected to a data lake.
Which tool should the consultant recommend to meet the client's requirements?

  • A. Tableau Catalog with Tableau Server Management Add-on
  • B. Tableau Catalog with Tableau Data Management Add-on
  • C. Tableau Prep Conductor
  • D. Tableau Catalog without Tableau Data Management Add-on

Answer: B

Explanation:
To effectively curate and document data for obtaining data lineage, particularly from a data source connected to a data lake, the recommended tool is:
* Tableau Catalog with Tableau Data Management Add-on: This add-on enhances the capabilities of Tableau Catalog, providing extensive features for data management, including detailed data lineage, impact analysis, and metadata management.
* Functionality: The Tableau Catalog with the Data Management Add-on allows users to see the full history and lineage of the data, trace its usage across all Tableau content, and understand dependencies.
It also facilitates better governance and transparency in data handling.
* Why Choose this Tool: For a client needing comprehensive data lineage and documentation capabilities, this add-on ensures that data stewards and users can maintain and utilize a well-managed data environment. It supports robust data governance practices necessary for large and complex data ecosystems like those typically associated with data lakes.
ReferencesThe recommendation is based on the functionalities offered by the Tableau Data Management Add-on, as described in Tableau's official documentation on managing and documenting data sources for enhanced governance and operational efficiency.


NEW QUESTION # 25
A client wants to produce a visualization to show quarterly profit growth and aggregated sales totals across a number of product categories from the data provided below.

Which set of charts should the consultant use to meet the client's requirements?

  • A. Line and bubble charts
  • B. Waterfall chart and tree map
  • C. Scatter plot and pie chart
  • D. Gantt and bar charts

Answer: B

Explanation:
To effectively display quarterly profit growth and aggregated sales totals across different product categories, a combination of a Waterfall chart and a Tree Map is recommended:
* Waterfall Chart: This chart type is excellent for visualizing the sequential growth or decline of profits across different quarters for each sub-category. It clearly shows how profits accumulate over time, highlighting both positive and negative changes, which makes it ideal for tracking profit growth or decline through the quarters.
* Tree Map: A Tree Map can efficiently display aggregated sales totals where each block size represents the total sales of a product category, providing a quick, visually impactful comparison across categories.
This is especially useful when the client wants to understand which categories contribute most to sales in a glanceable format.
Together, these charts provide a comprehensive overview of both profit trends over time (Waterfall Chart) and a comparative snapshot of sales performance across categories (Tree Map), meeting the client's need to analyze performance dynamics in a detailed yet consolidated manner.
ReferencesThese recommendations are based on common best practices for data visualization in Tableau, where specific chart types are chosen for their strengths in communicating certain types of data relationships and dynamics, as detailed in Tableau's official visualization guides.


NEW QUESTION # 26
......

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